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About

Ioannis Pitas is a distinguished researcher whose work spans computer vision, autonomous systems, and deep learning, with a particularly strong focus on Unmanned Aerial Vehicles (UAVs) and intelligent drone technologies. Over several decades, his research has evolved from foundational contributions in morphological shape representation — dating back to his 1991 work unifying classical object description techniques — to cutting-edge applications in autonomous aerial systems. Pitas has made significant contributions to UAV-based visual object detection and tracking, safe autonomous landing using lightweight deep neural networks, and drone cinematography, collectively accumulating over 150 citations across his most impactful recent works. His research addresses real-world challenges in surveillance, search and rescue, and human-drone interaction, including intuitive hand gesture control for autonomous UAVs. Notable achievements include developing multi-objective quaternion learning frameworks for 3D pose estimation and a suspect-and-investigate framework for automated parking violation detection embedded in drones. His broader influence extends to shaping the future of autonomous systems through participation in landmark panels such as the inaugural IEEE ICAS'21. Pitas's work consistently bridges theoretical rigor with practical deployment, making him a key figure in modern autonomous and human-centered intelligent systems research.